scienceclaw-generation

Scientific Generation Skill

Generate hypotheses, experimental designs, and scientific writing across all disciplines.

When to Use

• "Propose hypotheses for this research question"
• "Design an experiment to test..."
• "Draft a methods section for..."
• "Generate research questions for this topic"
• "Write an abstract for these findings"
• Planning new research directions

When NOT to Use

• Running data analysis (use code-execution + scipy-analysis)
• Literature searching (use literature-search)
• Verifying claims (use scienceclaw-verification)
• Pure information extraction (use scienceclaw-ie)

Generation Types

1. Hypothesis Generation

Follow the structured workflow:

1. Observation: State the observed phenomenon or gap
2. Literature Context: Reference existing knowledge and gaps
3. Hypothesis Statement: Formulate as testable H0/H1
4. Variables: Identify independent, dependent, and control variables
5. Predictions: State specific, measurable predictions
6. Falsifiability: Explain what would disprove the hypothesis
7. Novelty Assessment: Rate novelty (incremental/moderate/transformative)

Format: "If [independent variable] then [predicted effect on dependent variable] because [mechanism/rationale]"

2. Experimental Design

Include all components:

• Objective: Clear research question
• Design Type: RCT, factorial, quasi-experimental, etc.
• Sample: Size calculation (power analysis), selection criteria, randomization
• Variables: IV, DV, controls, confounds
• Protocol: Step-by-step procedure
• Analysis Plan: Statistical tests, significance thresholds
• Ethics: IRB/IACUC considerations
• Reproducibility Checklist: Materials, data sharing, pre-registration

3. Scientific Writing

Support all IMRaD sections:

• Introduction: Background, gap, objective, significance
• Methods: Detailed, reproducible protocol
• Results: Findings with statistical reporting
• Discussion: Interpretation, limitations, implications
• Abstract: Structured summary (Background, Methods, Results, Conclusions)

4. Research Question Generation

From a broad topic, generate:

• Descriptive questions (What/How/When)
• Comparative questions (differences between groups)
• Correlational questions (relationships between variables)
• Causal questions (cause-effect with mechanisms)

Quality Criteria

All generated content must:

1. Be grounded in existing scientific knowledge
2. Use discipline-appropriate terminology
3. Be specific and testable (for hypotheses)
4. Include feasibility assessment
5. Consider ethical implications
6. Acknowledge limitations and assumptions
7. Cite relevant foundational work when possible

Citation Format

When referencing prior work in generated content, use:

• Inline: (Author et al., Year) or [DOI]
• Note which citations need verification
• Distinguish confirmed vs. suggested references